Résumés des rapports de recherche

RR-2017-01 Transforming Prefix-Constrained or Controlled Rewrite SystemsNirina Andrianarivelo, Vivien Pelletier, Pierre RétyRésumé : We present two techniques for transforming any prefix-cons\-trained and any controlled term rewrite system into an ordinary rewrite system.
We prove that both transformations preserve the rewrite computations, and preserve termination.
In this way, prefix-constrained rewriting and controlled rewriting can be run, and termination can be checked, using the usual tools for ordinary rewriting.Mot(s) Clé(s) : controlled rewriting, prefix constrained rewriting, tree automaton.

RR-2017-02 Handling limits of high degree vertices in graph processing using MapReduce and PregelM. Al Hajj Hassan and Mostafa BamhaRésumé : Even if Pregel scales better than MapReduce in graph processing by reducing iteration's disk I/O, while offering an easy programming model using
"think like vertex" approach, large scale graph processing is still challenging in the presence of high degree vertices: Communication and
load imbalance among processing nodes can have disastrous effects on performance.
In this paper, we introduce a scalable MapReduce graph partitioning approach for high degree vertices using a master/slave partitioning
allowing to balance communication and computation among processing nodes during all the stages of graph processing. Cost analysis
and performance tests of this partitioning are given to show the effectiveness and the scalability of this approach in large scale systems.Mot(s) Clé(s) : Graph processing, High degree vertices, Data skew, MapReduce programming model, Pregel, Distributed file systems.

RR-2017-03 Concurrent Program Verification by Code Transformation: CorrectnessAllan Blanchard, Nikolai Kosmatov, Frédéric LoulergueRésumé : Frama-C is a software analysis framework that provides a common infrastructure
and a common behavioral specification language to plugins that implement various
static and dynamic analyses of C programs. Most plugins do not support concurrency.
We have proposed conc2seq, a Frama-C plugin based on program transformation,
capable to leverage the existing huge code base of plugins and to handle concurrent C
programs.
In this paper we formalize and sketch the proof of correctness of the program trans-
formation principle behind conc2seq, and present an effort towards the full mecha-
nization of both the formalization and proofs with the proof assistant Coq.Mot(s) Clé(s) :

RR-2017-05 Updating of RDF/S Databases under Negative and Tuple-Generating ConstraintsMirian Halfeld Ferrari and Dominique LaurentRésumé : In this paper, we address the issue of updating RDF/S
databases, in which constraints are imposed. Contrary to
standard approaches where constraints are restricted to those
inherently defined by the data model, we also consider constraints imposed by the particular application modelled by
the database. All these constraints fall in two categories,
called positive and negative, generalizing the well known key-
foreign key constraints.
Based on a chasing technique, we propose a deterministic update strategy which deals with sets of insertions and
deletions over RDF/S instances, while satisfying consistency
and minimal change requirements. The time complexity of
our approach is polynomial.Mot(s) Clé(s) :

RR-2017-06 Personalized Environment for Querying Semantic Knowledge Graphs: a MapReduce SolutionMostafa Bamha, Jacques Chabin, Mirian Halfeld Ferrari, Béatrice Markhoff, Thanh Binh NguyenRésumé : Querying according to a personalised context is an increas-
ingly required feature on semantic graph databases. We define contexts
by using constraints imposed on queries and not on data sources. No
correction trial is performed on an inconsistent database but answers
are ensured to be valid. Data confidence according to provenance is also
taken into account. As constraint validation and query evaluation are two
independent modules, our approach can be tested with di↵erent query
evaluators. This paper focus on a MapReduce query environment.Mot(s) Clé(s) : graph database, RDF, constraint, context, MapReduce.